4  bulkTCRseq: IMP-expanded clones

4.1 Set up workspace

# Libraries
library(dplyr)

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ forcats   1.0.0     ✔ readr     2.1.5
✔ ggplot2   3.5.1     ✔ stringr   1.5.1
✔ lubridate 1.9.4     ✔ tibble    3.2.1
✔ purrr     1.0.4     ✔ tidyr     1.3.1

── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(ggpointdensity)
library(ggplot2)
library(patchwork)
library(ggridges)

4.2 Load all clones

p101_betas_typed <- read.csv("p101_betas_merged_typed_Part3.csv")
p103_betas_typed <- read.csv("p103_betas_merged_typed_Part3.csv")
p104_betas_typed <- read.csv("p104_betas_merged_typed_Part3.csv")
p105_betas_typed <- read.csv("p105_betas_merged_typed_Part3.csv")
p106_betas_typed <- read.csv("p106_betas_merged_typed_Part3.csv")
p108_betas_typed <- read.csv("p108_betas_merged_typed_Part3.csv")
p109_betas_typed <- read.csv("p109_betas_merged_typed_Part3.csv")
p110_betas_typed <- read.csv("p110_betas_merged_typed_Part3.csv")
p111_betas_typed <- read.csv("p111_betas_merged_typed_Part3.csv")

4.3 Load cutoffs

cutoff_df <- read.csv("IMP_expanded_cuotff_Part3.csv")

p101_min_x <- cutoff_df %>%
  filter(Patient == "P101") %>%
  pull(invitro_exp_cutoff)
p103_min_x <- cutoff_df %>%
  filter(Patient == "P103") %>%
  pull(invitro_exp_cutoff)
p104_min_x <- cutoff_df %>%
  filter(Patient == "P104") %>%
  pull(invitro_exp_cutoff)
p105_min_x <- cutoff_df %>%
  filter(Patient == "P105") %>%
  pull(invitro_exp_cutoff)
p106_min_x <- cutoff_df %>%
  filter(Patient == "P106") %>%
  pull(invitro_exp_cutoff)
p108_min_x <- cutoff_df %>%
  filter(Patient == "P108") %>%
  pull(invitro_exp_cutoff)
p109_min_x <- cutoff_df %>%
  filter(Patient == "P109") %>%
  pull(invitro_exp_cutoff)
p110_min_x <- cutoff_df %>%
  filter(Patient == "P110") %>%
  pull(invitro_exp_cutoff)
p111_min_x <- cutoff_df %>%
  filter(Patient == "P111") %>%
  pull(invitro_exp_cutoff)

4.4 Reorder Type factor

p101_betas_typed <- p101_betas_typed %>%
  mutate(Type = factor(Type, levels = c("Post-Vaccine", "Post-Nivolumab", "Existing")))
p103_betas_typed <- p103_betas_typed %>%
  mutate(Type = factor(Type, levels = c("Post-Vaccine", "Post-Nivolumab", "Existing")))
p104_betas_typed <- p104_betas_typed %>%
  mutate(Type = factor(Type, levels = c("Post-Vaccine", "Post-Nivolumab", "Existing")))
p105_betas_typed <- p105_betas_typed %>%
  mutate(Type = factor(Type, levels = c("Post-Vaccine", "Post-Nivolumab", "Existing")))
p106_betas_typed <- p106_betas_typed %>%
  mutate(Type = factor(Type, levels = c("Post-Vaccine", "Post-Nivolumab", "Existing")))
p108_betas_typed <- p108_betas_typed %>%
  mutate(Type = factor(Type, levels = c("Post-Vaccine", "Post-Nivolumab", "Existing")))
p109_betas_typed <- p109_betas_typed %>%
  mutate(Type = factor(Type, levels = c("Post-Vaccine", "Post-Nivolumab", "Existing")))
p110_betas_typed <- p110_betas_typed %>%
  mutate(Type = factor(Type, levels = c("Post-Vaccine", "Post-Nivolumab", "Existing")))
p111_betas_typed <- p111_betas_typed %>%
  mutate(Type = factor(Type, levels = c("Post-Vaccine", "Post-Nivolumab", "Existing")))

4.5 Ridgeplot of in vitro expansion values with rug

# Create a rug of clones' expansion values
p101_rp <- p101_betas_typed %>%
  ggplot(aes(x = log2(max_fc_pool_vs_dmso), y = Type, fill = Type)) +
  geom_density_ridges(aes(point_color = factor(after_stat(x) > log2(p101_min_x)), point_alpha = factor(after_stat(x) > log2(p101_min_x))), jittered_points = TRUE,
    position = position_points_jitter(width = 0, height = 0, yoffset = -0.2), # Rug
    point_shape = '|', point_size = 3, #point_alpha = 0.7, 
    alpha = 0.7,
    bandwidth = 0.3, scale = 2) +
  scale_fill_manual(values = c("#0072B2", "darkgoldenrod3", "grey70")) +
  scale_discrete_manual(aesthetics = "point_color", values = c('black', "#920000FF"), guide = "none") +
  scale_discrete_manual(aesthetics = "point_alpha", values = c(0.1, 0.7), guide = "none") +
  xlab(expression(atop(italic("In vitro")~"expansion",~log[2]("PoolA,B peptides / DMSO")))) +
  ylab("Number of clones") +
  ggtitle("P101") +
  theme_classic() +
  theme(plot.title = element_text(hjust=0.5),
        axis.text.x = element_text(vjust=0)) + 
  geom_vline(xintercept = log2(p101_min_x), color = "black", linetype="dashed") +
  coord_cartesian(clip = "off")

p103_rp <- p103_betas_typed %>%
  ggplot(aes(x = log2(max_fc_pool_vs_dmso), y = Type, fill = Type)) +
  geom_density_ridges(aes(point_color = factor(after_stat(x) > log2(p103_min_x)), point_alpha = factor(after_stat(x) > log2(p103_min_x))), jittered_points = TRUE,
    position = position_points_jitter(width = 0, height = 0, yoffset = -0.2), # Rug
    point_shape = '|', point_size = 3, #point_alpha = 0.7, 
    alpha = 0.7,
    bandwidth = 0.3, scale = 2) +
  scale_fill_manual(values = c("#0072B2", "darkgoldenrod3", "grey70")) +
  scale_discrete_manual(aesthetics = "point_color", values = c('black', "#920000FF"), guide = "none") +
  scale_discrete_manual(aesthetics = "point_alpha", values = c(0.1, 0.7), guide = "none") +
  xlab(expression(atop(italic("In vitro")~"expansion",~log[2]("PoolA,B peptides / DMSO")))) +
  ylab("Number of clones") +
  ggtitle("P103") +
  theme_classic() +
  theme(plot.title = element_text(hjust=0.5),
        axis.text.x = element_text(vjust=0)) + 
  geom_vline(xintercept = log2(p103_min_x), color = "black", linetype="dashed") +
  coord_cartesian(clip = "off")

p104_rp <- p104_betas_typed %>%
  ggplot(aes(x = log2(max_fc_pool_vs_dmso), y = Type, fill = Type)) +
  geom_density_ridges(aes(point_color = factor(after_stat(x) > log2(p104_min_x)), point_alpha = factor(after_stat(x) > log2(p104_min_x))), jittered_points = TRUE,
    position = position_points_jitter(width = 0, height = 0, yoffset = -0.2), # Rug
    point_shape = '|', point_size = 3, #point_alpha = 0.7, 
    alpha = 0.7,
    bandwidth = 0.3, scale = 2) +
  scale_fill_manual(values = c("#0072B2", "darkgoldenrod3", "grey70")) +
  scale_discrete_manual(aesthetics = "point_color", values = c('black', "#920000FF"), guide = "none") +
  scale_discrete_manual(aesthetics = "point_alpha", values = c(0.1, 0.7), guide = "none") +
  xlab(expression(atop(italic("In vitro")~"expansion",~log[2]("PoolA,B peptides / DMSO")))) +
  ylab("Number of clones") +
  ggtitle("P104") +
  theme_classic() +
  theme(plot.title = element_text(hjust=0.5),
        axis.text.x = element_text(vjust=0)) + 
  geom_vline(xintercept = log2(p104_min_x), color = "black", linetype="dashed") +
  coord_cartesian(clip = "off")

p105_rp <- p105_betas_typed %>%
  ggplot(aes(x = log2(max_fc_pool_vs_dmso), y = Type, fill = Type)) +
  geom_density_ridges(aes(point_color = factor(after_stat(x) > log2(p105_min_x)), point_alpha = factor(after_stat(x) > log2(p105_min_x))), jittered_points = TRUE,
    position = position_points_jitter(width = 0, height = 0, yoffset = -0.2), # Rug
    point_shape = '|', point_size = 3, #point_alpha = 0.7, 
    alpha = 0.7,
    bandwidth = 0.3, scale = 2) +
  scale_fill_manual(values = c("#0072B2", "darkgoldenrod3", "grey70")) +
  scale_discrete_manual(aesthetics = "point_color", values = c('black', "#920000FF"), guide = "none") +
  scale_discrete_manual(aesthetics = "point_alpha", values = c(0.1, 0.7), guide = "none") +
  xlab(expression(atop(italic("In vitro")~"expansion",~log[2]("PoolA,B peptides / DMSO")))) +
  ylab("Number of clones") +
  ggtitle("P105") +
  theme_classic() +
  theme(plot.title = element_text(hjust=0.5),
        axis.text.x = element_text(vjust=0)) + 
  geom_vline(xintercept = log2(p105_min_x), color = "black", linetype="dashed") +
  coord_cartesian(clip = "off")

p106_rp <- p106_betas_typed %>%
  ggplot(aes(x = log2(max_fc_pool_vs_dmso), y = Type, fill = Type)) +
  geom_density_ridges(aes(point_color = factor(after_stat(x) > log2(p106_min_x)), point_alpha = factor(after_stat(x) > log2(p106_min_x))), jittered_points = TRUE,
    position = position_points_jitter(width = 0, height = 0, yoffset = -0.2), # Rug
    point_shape = '|', point_size = 3, #point_alpha = 0.7, 
    alpha = 0.7,
    bandwidth = 0.3, scale = 2) +
  scale_fill_manual(values = c("#0072B2", "darkgoldenrod3", "grey70")) +
  scale_discrete_manual(aesthetics = "point_color", values = c('black', "#920000FF"), guide = "none") +
  scale_discrete_manual(aesthetics = "point_alpha", values = c(0.1, 0.7), guide = "none") +
  xlab(expression(atop(italic("In vitro")~"expansion",~log[2]("PoolA,B peptides / DMSO")))) +
  ylab("Number of clones") +
  ggtitle("P106") +
  theme_classic() +
  theme(plot.title = element_text(hjust=0.5),
        axis.text.x = element_text(vjust=0)) + 
  geom_vline(xintercept = log2(p106_min_x), color = "black", linetype="dashed") +
  coord_cartesian(clip = "off")

p108_rp <- p108_betas_typed %>%
  ggplot(aes(x = log2(max_fc_pool_vs_dmso), y = Type, fill = Type)) +
  geom_density_ridges(aes(point_color = factor(after_stat(x) > log2(p108_min_x)), point_alpha = factor(after_stat(x) > log2(p108_min_x))), jittered_points = TRUE,
    position = position_points_jitter(width = 0, height = 0, yoffset = -0.2), # Rug
    point_shape = '|', point_size = 3, #point_alpha = 0.7, 
    alpha = 0.7,
    bandwidth = 0.3, scale = 2) +
  scale_fill_manual(values = c("#0072B2", "darkgoldenrod3", "grey70")) +
  scale_discrete_manual(aesthetics = "point_color", values = c('black', "#920000FF"), guide = "none") +
  scale_discrete_manual(aesthetics = "point_alpha", values = c(0.1, 0.7), guide = "none") +
  xlab(expression(atop(italic("In vitro")~"expansion",~log[2]("PoolA,B peptides / DMSO")))) +
  ylab("Number of clones") +
  ggtitle("P108") +
  theme_classic() +
  theme(plot.title = element_text(hjust=0.5),
        axis.text.x = element_text(vjust=0)) + 
  geom_vline(xintercept = log2(p108_min_x), color = "black", linetype="dashed") +
  coord_cartesian(clip = "off")

p109_rp <- p109_betas_typed %>%
  ggplot(aes(x = log2(max_fc_pool_vs_dmso), y = Type, fill = Type)) +
  geom_density_ridges(aes(point_color = factor(after_stat(x) > log2(p109_min_x)), point_alpha = factor(after_stat(x) > log2(p109_min_x))), jittered_points = TRUE,
    position = position_points_jitter(width = 0, height = 0, yoffset = -0.2), # Rug
    point_shape = '|', point_size = 3, #point_alpha = 0.7, 
    alpha = 0.7,
    bandwidth = 0.3, scale = 2) +
  scale_fill_manual(values = c("#0072B2", "darkgoldenrod3", "grey70")) +
  scale_discrete_manual(aesthetics = "point_color", values = c('black', "#920000FF"), guide = "none") +
  scale_discrete_manual(aesthetics = "point_alpha", values = c(0.1, 0.7), guide = "none") +
  xlab(expression(atop(italic("In vitro")~"expansion",~log[2]("PoolA,B peptides / DMSO")))) +
  ylab("Number of clones") +
  ggtitle("P109") +
  theme_classic() +
  theme(plot.title = element_text(hjust=0.5),
        axis.text.x = element_text(vjust=0)) + 
  geom_vline(xintercept = log2(p109_min_x), color = "black", linetype="dashed") +
  coord_cartesian(clip = "off")

p110_rp <- p110_betas_typed %>%
  ggplot(aes(x = log2(max_fc_pool_vs_dmso), y = Type, fill = Type)) +
  geom_density_ridges(aes(point_color = factor(after_stat(x) > log2(p110_min_x)), point_alpha = factor(after_stat(x) > log2(p110_min_x))), jittered_points = TRUE,
    position = position_points_jitter(width = 0, height = 0, yoffset = -0.2), # Rug
    point_shape = '|', point_size = 3, #point_alpha = 0.7, 
    alpha = 0.7,
    bandwidth = 0.3, scale = 2) +
  scale_fill_manual(values = c("#0072B2", "darkgoldenrod3", "grey70")) +
  scale_discrete_manual(aesthetics = "point_color", values = c('black', "#920000FF"), guide = "none") +
  scale_discrete_manual(aesthetics = "point_alpha", values = c(0.1, 0.7), guide = "none") +
  xlab(expression(atop(italic("In vitro")~"expansion",~log[2]("PoolA,B peptides / DMSO")))) +
  ylab("Number of clones") +
  ggtitle("P110") +
  theme_classic() +
  theme(plot.title = element_text(hjust=0.5),
        axis.text.x = element_text(vjust=0)) + 
  geom_vline(xintercept = log2(p110_min_x), color = "black", linetype="dashed") +
  coord_cartesian(clip = "off")

p111_rp <- p111_betas_typed %>%
  ggplot(aes(x = log2(max_fc_pool_vs_dmso), y = Type, fill = Type)) +
  geom_density_ridges(aes(point_color = factor(after_stat(x) > log2(p111_min_x)), point_alpha = factor(after_stat(x) > log2(p111_min_x))), jittered_points = TRUE,
    position = position_points_jitter(width = 0, height = 0, yoffset = -0.2), # Rug
    point_shape = '|', point_size = 3, #point_alpha = 0.7, 
    alpha = 0.7,
    bandwidth = 0.3, scale = 2.5) +
  scale_fill_manual(values = c("#0072B2", "darkgoldenrod3", "grey70")) +
  scale_discrete_manual(aesthetics = "point_color", values = c('black', "#920000FF"), guide = "none") +
  scale_discrete_manual(aesthetics = "point_alpha", values = c(0.1, 0.7), guide = "none") +
  xlab(expression(atop(italic("In vitro")~"expansion",~log[2]("PoolA,B peptides / DMSO")))) +
  ylab("Number of clones") +
  ggtitle("P111") +
  theme_classic() +
  theme(plot.title = element_text(hjust=0.5),
        axis.text.x = element_text(vjust=0)) + 
  geom_vline(xintercept = log2(p111_min_x), color = "black", linetype="dashed") +
  coord_cartesian(clip = "off")

4.6 Patchwork together for Fig 3E

rp <- p101_rp + p103_rp + p104_rp + p105_rp + p106_rp + p108_rp + p109_rp + p110_rp + p111_rp + plot_layout(guides = "collect", axis_titles = "collect")

rp 

4.7 Get session info

sessionInfo()

R version 4.3.2 (2023-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Rocky Linux 8.10 (Green Obsidian)

Matrix products: default
BLAS/LAPACK: /usr/lib64/libopenblasp-r0.3.15.so;  LAPACK version 3.9.0

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

time zone: America/New_York
tzcode source: system (glibc)

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] ggridges_0.5.6       patchwork_1.3.0      ggpointdensity_0.1.0
 [4] lubridate_1.9.4      forcats_1.0.0        stringr_1.5.1       
 [7] purrr_1.0.4          readr_2.1.5          tidyr_1.3.1         
[10] tibble_3.2.1         ggplot2_3.5.1        tidyverse_2.0.0     
[13] dplyr_1.1.4         

loaded via a namespace (and not attached):
 [1] gtable_0.3.6      jsonlite_1.8.9    compiler_4.3.2    tidyselect_1.2.1 
 [5] scales_1.3.0      fastmap_1.2.0     R6_2.6.1          labeling_0.4.3   
 [9] generics_0.1.3    knitr_1.49        htmlwidgets_1.6.4 munsell_0.5.1    
[13] pillar_1.10.1     tzdb_0.5.0        rlang_1.1.5       stringi_1.8.4    
[17] xfun_0.50         timechange_0.3.0  cli_3.6.3         withr_3.0.2      
[21] magrittr_2.0.3    digest_0.6.37     grid_4.3.2        rstudioapi_0.17.1
[25] hms_1.1.3         lifecycle_1.0.4   vctrs_0.6.5       evaluate_1.0.1   
[29] glue_1.8.0        farver_2.1.2      colorspace_2.1-1  rmarkdown_2.29   
[33] tools_4.3.2       pkgconfig_2.0.3   htmltools_0.5.8.1